Trustable DP-750 - Implementing Data Engineering Solutions Using Azure Databricks Valid Test Cost

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Microsoft DP-750 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare and process data30-35%- Data transformation and modeling
  • 1. Delta Lake table design and SCD patterns
    • 2. SQL and PySpark transformations
      • 3. Joins, aggregations, and normalization/denormalization
        - Data quality and validation
        • 1. Pipeline expectations and data quality constraints
          • 2. Handling nulls, duplicates, and missing data
            • 3. Schema enforcement and validation rules
              - Data ingestion
              • 1. Batch ingestion using COPY INTO and CTAS
                • 2. Streaming ingestion using Spark Structured Streaming
                  • 3. Auto Loader and CDC ingestion patterns
                    Topic 2: Secure and govern data using Unity Catalog15-20%- Access control and policies
                    • 1. Row-level and column-level security
                      • 2. Tags and policy enforcement
                        • 3. Attribute-based access control (ABAC)
                          - Data governance fundamentals
                          • 1. Catalog, schema, and table management
                            • 2. Data lineage and auditing
                              Topic 3: Configure and manage Azure Databricks environments15-20%- Workspace and compute configuration
                              • 1. Cluster types and configuration (job, all-purpose, serverless)
                                • 2. Runtime, Spark, and Photon configuration
                                  • 3. Autoscaling, termination, and performance tuning
                                    - Security and authentication setup
                                    • 1. Service principals and managed identities
                                      • 2. Azure Key Vault integration
                                        • 3. Access control for compute resources
                                          Topic 4: Deploy and manage data pipelines and workloads30-35%- Lakehouse architecture operations
                                          • 1. Delta Live Tables pipelines
                                            • 2. Delta Lake optimization and clustering strategies
                                              - Pipeline design and orchestration
                                              • 1. Databricks Jobs and Workflows
                                                • 2. Notebook-based vs declarative pipelines
                                                  - Operational reliability
                                                  • 1. Monitoring and logging (Azure Monitor integration)
                                                    • 2. Error handling and retries

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                                                      Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions (Q53-Q58):

                                                      NEW QUESTION # 53
                                                      You have an Azure Databricks workspace that is enabled for Unity Catalog. You plan to run the following PySpark code.

                                                      For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

                                                      Answer:

                                                      Explanation:

                                                      Explanation:
                                                      For HOTSPOT questions, each statement must be evaluated against the actual PySpark code shown in the answer area. Key evaluation principles:
                                                      DataFrames are immutable - every transformation returns a new DataFrame; the original is unchanged.
                                                      Transformations (filter, select, groupBy, join) are lazy and only execute when an action (show, count, write) is called.
                                                      Null handling: df.filter(col != None) is incorrect in PySpark due to SQL null semantics; use col.isNotNull() or dropna() instead. Schema changes: using mergeSchema=true or schema evolution handles new columns.
                                                      Write modes: ' overwrite ' replaces existing data; ' append ' adds to it.
                                                      Always check whether the code uses the correct Delta format (.format( ' delta ' )), Unity Catalog three-part naming, and whether write operations include a checkpointLocation for streaming queries. Evaluate each statement strictly on what the code does, not on what it might intend to do.
                                                      Reference: https://learn.microsoft.com/en-us/azure/databricks/pyspark/basics


                                                      NEW QUESTION # 54
                                                      Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
                                                      After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
                                                      You have an Azure Databricks workspace named Workspace1 that contains a lakehouse and is enabled for Unity Catalog.
                                                      You have a connection to a Microsoft SQL Server database named DB1.
                                                      You need to expose the schemas and tables of DB1 to meet the following requirements:
                                                      - The schemas and tables can be queried in Databricks.
                                                      - The schemas and tables appear alongside other Unity Catalog objects.
                                                      - The data is NOT copied into Databricks-managed storage.
                                                      Solution: You create a Lakeflow Connect pipeline and connect it to DB1.
                                                      Does this meet the goal?

                                                      Answer: A

                                                      Explanation:
                                                      Correct:
                                                      * You create a foreign catalog in Catalog Explorer.
                                                      You should create a Foreign Catalog using Lakehouse Federation.
                                                      Data Copying: Lakehouse Federation queries data directly in the source SQL Server without moving or copying it.
                                                      Seamless Integration: The database schemas and tables appear right inside Unity Catalog alongside your other data objects.Real-time Access: It provides immediate access to live SQL Server data.
                                                      Incorrect:
                                                      * You create a Databricks access connector.
                                                      * You create a Lakeflow Connect pipeline and connect it to DB1.
                                                      Data Copying: Lakeflow Connect is an ingestion tool that physically replicates and copies data into Databricks-managed storage (Delta tables).
                                                      Storage Costs: It violates your requirement to keep data out of Databricks storage.
                                                      * You create a new native catalog in Unity Catalog.
                                                      Note:
                                                      To expose the external SQL Server database in Unity Catalog without copying the data, you must use Lakehouse Federation.
                                                      Here are the step-by-step actions you need to take:
                                                      1. Create a Connection
                                                      Create a securable object in Unity Catalog that specifies the path and credentials to access the SQL Server database.
                                                      Go to Catalog Explorer or use SQL.
                                                      Select External Data > Connections.
                                                      Create a connection using the SQL Server connection details (URL, host, port, and database credentials).
                                                      *-> 2. Create a Foreign Catalog
                                                      Create a specific type of catalog in Unity Catalog that mirrors the external database.
                                                      Use the CREATE FOREIGN CATALOG SQL command or the Catalog Explorer UI.
                                                      Link this foreign catalog directly to the connection you created in step 1.
                                                      3. Query the DataOnce the foreign catalog is created, Unity Catalog automatically syncs the schemas and tables from SQL Server.
                                                      Reference:
                                                      https://docs.databricks.com/gcp/en/database-objects/


                                                      NEW QUESTION # 55
                                                      You have an Azure Databricks workspace named Workspace1 that is attached to a Unity Catalog metastore named metastore1 You need to register an Azure Storage account named account1 that has a hierarchical namespace enabled as an external location The external location must use a managed identity to authenticate to account1 and the solution must follow the principle of least privilege.
                                                      Which three actions should you perform in sequence' To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

                                                      Answer:

                                                      Explanation:

                                                      Explanation:
                                                      Registering an ADLS Gen2 account as an external location in Unity Catalog requires three steps in a specific order:
                                                      Step 1: Create a Databricks Access Connector. This Azure resource wraps a system-assigned or user-assigned managed identity. It is the credential-less authentication bridge between Databricks and Azure Storage - no SAS tokens or access keys are stored anywhere in the workspace.
                                                      Step 2: Create a Storage Credential in Unity Catalog that references the Access Connector. This object tells Unity Catalog 'use this identity when accessing storage.' The Storage Credential is the reusable authentication object.
                                                      Step 3: Create an External Location that maps a Unity Catalog path to the specific ADLS Gen2 container using the Storage Credential. This is the object that grants Databricks users access to files under that path, and it respects the principle of least privilege by scoping access to a specific container.
                                                      Reference: https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/storage-credentials


                                                      NEW QUESTION # 56
                                                      Hotspot Question
                                                      You have an Azure Databricks workspace that is enabled for Unity Catalog.
                                                      You need to create an external volume named Volume1 in an existing schema. Volume1 must expose files from an Azure Storage container. The solution must meet the following requirements:
                                                      - Ensure that authentication does NOT require storing credentials in
                                                      Databricks.
                                                      - Ensure that users can access the files, but NOT modify the files.
                                                      - Follow the principle of least privilege.
                                                      Which type of authentication should you configure, and which permission should you grant to the users? To answer, select the appropriate options in the answer area.
                                                      NOTE: Each correct selection is worth one point.

                                                      Answer:

                                                      Explanation:


                                                      NEW QUESTION # 57
                                                      Hotspot Question
                                                      You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a catalog named catalog1.
                                                      You have a group named group1.
                                                      You plan to create a schema named schema1 in catalog1.
                                                      You need to ensure that group1 meets the following requirements:
                                                      - Can create tables in schema1
                                                      - Can modify and query tables
                                                      - Cannot grant permissions for the schema and its objects
                                                      How should you complete the SQL statements? To answer, select the appropriate options in the answer area.
                                                      NOTE: Each correct selection is worth one point.

                                                      Answer:

                                                      Explanation:


                                                      NEW QUESTION # 58
                                                      ......

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